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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

MEUMAPPS (C++ Version)

Many materials, metal alloys in particular, have features on the on micrometer or nanometer scale that have a large impact on the properties of the material. These features are known as the microstructure of the material. Understanding why and how the microstructure forms in a material is of fundamental scientific interest as well as of significant technological interest. The capability to predict microstructure evolution in a material allows the intentional design of microstructures and hence the intentional design of material properties. The phase-field method is one of the leading methods for predicting microstructure evolution. One of the most significant problems for phase-field models is their computational expense. Even limited phase-field simulations can easily require thousands of CPU core-hours to complete, which significantly limits their use. This code provides both a general framework for creating scalable, GPU-accelerated phase-field model applications as well as several applications themselves. The code is capable of using hundreds of GPUs efficiently, which greatly reduces the time required to perform simulations. The code is written with an emphasis on performance portability, that is the ability for the code to run efficiently on a number of different computing architectures without modification of the source code. The performance portability of this code is primarily enabled through the use of two libraries, Kokkos (performance portable data structures and execution patterns) and heFFTe (performance portable distributed 3D fast Fourier transforms). The code consists of a core library, applications, and tests. The core library includes shared functionality between applications. This includes interfaces with fast Fourier transform (FFT) libraries such as heFFTe, data structures based on Kokkos, file input and output capabilities, and a solver for infinitesimal strain mechanical equilibrium problems. Five applications are included in the code. The flagship application is the MEUMAPPS-SS application, which implements the Kim-Kim-Suzuki phase-field model for precipitation for an arbitrary number of phases and components in a metal alloy. Five simpler applications are also included that solve the Eshelby inclusion problem, Allen-Cahn equation, the coupled Allen-Cahn and diffusion equations, and the Cahn-Hilliard equation. The code includes two applications to solve the Cahn-Hilliard equation, one with constant-step-size first-order time integration and the second with adaptive high-order time integration.

DeWitt, Stephen [Oak Ridge National Lab. (ORNL), O↗
DOE OSTI2021

The Making of a Metric: Co-Producing Decision-Relevant Climate Science

Developing decision-relevant science for adaptation requires the identification of climatic parameters that are both actionable for practitioners as well as tractable for modelers. In many sectors, these decision-relevant climatic metrics and the approaches that enable their identification remain largely unknown. “Co-production” of science with scientists and decision-makers is one potential way to identify these metrics, but there is little research describing specific and successful co-production approaches. This paper examines the negotiations and outcomes from Project Hyperion, wherein scientists and water managers jointly developed decision-relevant climatic metrics for adaptive water management. We identify successful co-production strategies by analyzing the project’s numerous back-and-forth engagements and tracing the evolution of the science during these engagements. We found that effective mediation between scientists and managers needed dedicated “boundary spanners” with significant modeling expertise. Translating practitioners’ information needs into tractable climatic metrics required direct and indirect methods of eliciting knowledge. We identified four indirect methods that were particularly salient for extracting tacitly held knowledge and enabling shared learning: developing a hierarchical framework linking management issues with metrics, starting discussions from the planning challenges, collaboratively exploring the planning relevance of new scientific capabilities, and using analogies of other “good” metrics. The decision-relevant metrics we developed provide insights into advancing adaptation-relevant climate science in the water sector. The co-production strategies we identified can be used to design and implement productive scientist–decision-maker interactions. Overall, the approaches and metrics we developed can help climate science to expand in new and more use-inspired directions.

Planning↗
DOE OSTI2024

DECOVALEX-2023: Task G, SAFENET Final Report

DECOVALEX Task G deals with fracture mechanics at several scales using a combined approach of experimental work, related model development, benchmarking and experimental analysis. Fig. 0.1 provides a graphical abstract for Task G. The experimental basis for the related mechanical (M), hydro-mechanical (HM), and thermo-mechanical (TM) processes comes from the rock mechanics laboratories of Universities of Freiberg (TUBAF) and Edinburgh, as well as the Korea Institute of Civil Engineering and Building Technology (KICT). The experimental work in the rock laboratories is closely linked to the underground research laboratories (URLs) Reiche Zeche (Germany), KURT (Korea), and Mont Terri (Switzerland). The scientific key questions are related to fracture permeability evolution under THM conditions, anisotropy effects on fracturing processes, and thermal fracture slip, which are being addressed in specific steps of the task. A large variety of numerical methods have been developed and applied for experimental analysis, ranging from continuum to discontinuum approaches. A detailed comparison of mechanical and hydro-mechanical processes is given in the section 3 via the benchmarking exercises. As a result of DECOVALEX-2023 Task G we further improved our understanding and predictability of fracturing processes under THM conditions. This was based on robust numerical simulation methods and in-depth experimental analysis.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Photo-zSNthesis: Converting Type Ia Supernova Lightcurves to Redshift Estimates via Deep Learning

Abstract Upcoming photometric surveys will discover tens of thousands of Type Ia supernovae (SNe Ia), vastly outpacing the capacity of our spectroscopic resources. In order to maximize the scientific return of these observations in the absence of spectroscopic information, we must accurately extract key parameters, such as SN redshifts, with photometric information alone. We present Photo- z SNthesis, a convolutional neural network-based method for predicting full redshift probability distributions from multi-band supernova lightcurves, tested on both simulated Sloan Digital Sky Survey (SDSS) and Vera C. Rubin Legacy Survey of Space and Time data as well as observed SDSS SNe. We show major improvements over predictions from existing methods on both simulations and real observations as well as minimal redshift-dependent bias, which is a challenge due to selection effects, e.g., Malmquist bias. Specifically, we show a 61× improvement in prediction bias 〈Δ z 〉 on PLAsTiCC simulations and 5× improvement on real SDSS data compared to results from a widely used photometric redshift estimator, LCFIT+Z. The PDFs produced by this method are well constrained and will maximize the cosmological constraining power of photometric SNe Ia samples.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1993

Hubble Space Telescope COSTAR asphere verification with a modified computer-generated hologram interferometer

To correct for the spherical aberration in the Hubble Space Telescope primary mirror, five anamorphic aspheric mirrors representing correction for three scientific instruments have been fabricated as part of the development of the corrective-optics space telescope axial-replacement instrument (COSTAR). During the acceptance tests of these mirrors at the vendor, a quick and simple method for verifying the asphere surface figure was developed. The technique has been used on three of the aspheres relating to the three instrument prescriptions. Results indicate that the three aspheres are correct to the limited accuracy expected of this test.

Feinberg, L.↗
NASA NTRS1990

Computational methods and software systems for dynamics and control of large space structures

This final report on computational methods and software systems for dynamics and control of large space structures covers progress to date, projected developments in the final months of the grant, and conclusions. Pertinent reports and papers that have not appeared in scientific journals (or have not yet appeared in final form) are enclosed. The grant has supported research in two key areas of crucial importance to the computer-based simulation of large space structure. The first area involves multibody dynamics (MBD) of flexible space structures, with applications directed to deployment, construction, and maneuvering. The second area deals with advanced software systems, with emphasis on parallel processing. The latest research thrust in the second area, as reported here, involves massively parallel computers.

Park, K. C.↗
NASA NTRS2001

Fresnel Lens

Fresnel lenses span the full range of sizes from lens a few micrometers in diameter to lens several meters in diameter. These lenses are utilized in various fields including optical communication, theatrical lighting, office equipment, video entertainment systems, solar concentrators, and scientific research instruments. These lenses function either as diffractive or refractive optical elements depending on the geometrical feature size of the lens. The basic functions of these lenses is described followed by an overview of fabrication methods. A summary of applications is then provided illustrating the rich variety of applications for which fresnel lenses may be designed to fulfill.

Watson, Michael D.↗
NASA NTRS2000

Hummingbird Comet Nucleus Analysis Mission

Hummingbird is a highly focused scientific mission, proposed to NASA s Discovery Program, designed to address the highest priority questions in cometary science-that of the chemical composition of the cometary nucleus. After rendezvous with the comet, Hummingbird would first methodically image and map the comet, then collect and analyze dust, ice and gases from the cometary atmosphere to enrich characterization of the comet and support landing site selection. Then, like its namesake, Hummingbird would carefully descend to a pre-selected surface site obtaining a high-resolution image, gather a surface material sample, acquire surface temperature and then immediately return to orbit for detailed chemical and elemental analyses followed by a high resolution post-sampling image of the site. Hummingbird s analytical laboratory contains instrumentation for a comprehensive molecular and elemental analysis of the cometary nucleus as well as an innovative surface sample acquisition device.

Kojiro, Daniel↗
NASA NTRS1992

Something is wrong with climate theory

We frequently forget that there is more to science than the making of a more precise measurement or a more elaborate calculation. It is even more than applying to new problems the methods that worked on old problems. These activities, which keep most of us busy most of the time, are important, but the new and unexpected discoveries are more important. And many radically new discoveries arise from scientific puzzles, the "anomalies." We believe that studies of past climates have exposed an anomaly that deserves attention and that may result in a fundamentally new understanding of the climate system. The poles have been much warmer throughout much of Earth's history than they are now. Ice-age episodes with durations of millions of years have been separated by periods of hundreds of millions of years that have left little or no evidence of polar ice sheets. The data are best for the most recent of these ice-free episodes so we will concentrate on the Eocene.

Non-NASA Center↗
NASA NTRS2005

Preparing for the Dawn Mission to Vesta and Ceres

The Dawn project is progressing toward its 2006 launch on a mission to orbit main belt asteroids (4) Vesta and (1) Ceres. Designed to provide insights into important questions about the evolution of the solar system, Dawn will spend more than 0.5 years in orbit about each of these bodies. This challenging mission is enabled by an ion propulsion system. In contrast to missions that use conventional chemical propulsion, the use of this system couples flight system mass and power , thereby requiring different methods of managing these and other technical resources. Now that the project is nearing launch, the refinement of resource estimates allows the identification of excess margin, which is being applied in novel ways to increase the scientific potential of the mission. The unusual relationship of the margins is described, and progress in preparing for the mission is presented.

Dawn↗
NASA NTRS2002

WOBBLE: A Proposed Mission to Characterize Past and Present Water on Mars

WOBBLE ("Water Observations from a Balloon Borne Light Explorer") is a mission concept study for a small robotic probe to explore Mars and to accomplish a scientific mission compatible with the goals of the NASA Code S enterprise. The detection of past or present water is a crucial goal for Mars exploration, representing a cross-cutting science theme relevant to past or extant life, climate history, sample return missions and eventual human exploration. The WOBBLE mission concept was developed to study evidence of water using in-situ detection methods. The features on Mars most suited to this investigation are the gullies identified by Malin and Edgett as evidence for recent, near-surface runoff of liquid water. These features are typically located on the inside face of crater rims, where the local slope angle is at or near the angle of repose. This makes the terrain difficult or impossible to access with conventional wheeled rover technology. Combined with the small size of the gullies in relation to a standard landing error ellipse, scientific investigation of these features requires a new approach to surface mobility. WOBBLE uses a low-altitude balloon-borne platform to traverse the surface from the landing site, to the investigation site, and then rise up the slope to investigate the regions of interest at close range. Of the mobility technologies available for near-term Mars exploration, only a balloon platform is capable of a well targeted, detailed sampling of the gully regions over periods of days or more. The science approach embodied in WOBBLE is two-pronged, designed to investigate both the historical evidence of liquid water utilizing high-resolution geomorphology and the characterization of mineral deposits, and present subsurface liquid water using radar sounding techniques. The WOBBLE balloon is a high-pressure hydrogen gas design, 24 meters in diameter and lifting a total payload of 130 kg, including a high-resolution camera/IR imager, Raman spectrometer, and a ground penetrating radar (GPR) sounder. The stowed balloon and payload are designed to fit within the current airbag delivery system being built for the Mars Exploration Rovers. Characterization of local meteorological conditions and wind is made over the initial sols following landing and before balloon inflation. Following balloon inflation and launch, a controlled, targeted approach toward the identified regions of interest is made in a series of several low-altitude "hops," with the balloon tethered to the ground between the hop intervals. A "snake" system is used to control the altitude to a few tens of meters above the local ground level. Enroute to the target gully, GPR soundings and Raman spectroscopy measurements study past or present water, while continued camera bearings and meteorological measurements refine the next "hop" trajectory. Once at the gully/outflow region, GPR and Raman soundings continue while the camera obtains detailed, approx. 0.5 cm images for geomorphology studies. The WOBBLE concept is applicable to Mars Scout, Mars Surveyor, or Discovery class missions.

Udrea, Bogdan↗
NASA NTRS1999

Parallelization of the Physical-Space Statistical Analysis System (PSAS)

Atmospheric data assimilation is a method of combining observations with model forecasts to produce a more accurate description of the atmosphere than the observations or forecast alone can provide. Data assimilation plays an increasingly important role in the study of climate and atmospheric chemistry. The NASA Data Assimilation Office (DAO) has developed the Goddard Earth Observing System Data Assimilation System (GEOS DAS) to create assimilated datasets. The core computational components of the GEOS DAS include the GEOS General Circulation Model (GCM) and the Physical-space Statistical Analysis System (PSAS). The need for timely validation of scientific enhancements to the data assimilation system poses computational demands that are best met by distributed parallel software. PSAS is implemented in Fortran 90 using object-based design principles. The analysis portions of the code solve two equations. The first of these is the "innovation" equation, which is solved on the unstructured observation grid using a preconditioned conjugate gradient (CG) method. The "analysis" equation is a transformation from the observation grid back to a structured grid, and is solved by a direct matrix-vector multiplication. Use of a factored-operator formulation reduces the computational complexity of both the CG solver and the matrix-vector multiplication, rendering the matrix-vector multiplications as a successive product of operators on a vector. Sparsity is introduced to these operators by partitioning the observations using an icosahedral decomposition scheme. PSAS builds a large (approx. 128MB) run-time database of parameters used in the calculation of these operators. Implementing a message passing parallel computing paradigm into an existing yet developing computational system as complex as PSAS is nontrivial. One of the technical challenges is balancing the requirements for computational reproducibility with the need for high performance. The problem of computational reproducibility is well known in the parallel computing community. It is a requirement that the parallel code perform calculations in a fashion that will yield identical results on different configurations of processing elements on the same platform. In some cases this problem can be solved by sacrificing performance. Meeting this requirement and still achieving high performance is very difficult. Topics to be discussed include: current PSAS design and parallelization strategy; reproducibility issues; load balance vs. database memory demands, possible solutions to these problems.

Larson, J. W.↗
DOE OSTI2020

The Role of Machine Learning in the Understanding and Design of Materials

Developing algorithmic approaches for the rational design and discovery of materials can enable us to systematically find novel materials, which can have huge technological and social impact. However, such rational design requires a holistic perspective over the full multistage design process, which involves exploring immense materials spaces, their properties, and process design and engineering as well as a techno-economic assessment. The complexity of exploring all of these options using conventional scientific approaches seems intractable. Instead, novel tools from the field of machine learning can potentially solve some of our challenges on the way to rational materials design. Here we review some of the chief advancements of these methods and their applications in rational materials design, followed by a discussion on some of the main challenges and opportunities we currently face together with our perspective on the future of rational materials design and discovery.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Model-Form Epistemic Uncertainty Quantification for Modeling with Differential Equations: Application to Epidemiology

Modeling real-world phenomena to any degree of accuracy is a challenge that the scientific research community has navigated since its foundation. Lack of information and limited computational and observational resources necessitate modeling assumptions which, when invalid, lead to model-form error (MFE). The work reported herein explored a novel method to represent model-form uncertainty (MFU) that combines Bayesian statistics with the emerging field of universal differential equations (UDEs). The fundamental principle behind UDEs is simple: use known equational forms that govern a dynamical system when you have them; then incorporate data-driven approaches – in this case neural networks (NNs) – embedded within the governing equations to learn the interacting terms that were underrepresented. Utilizing epidemiology as our motivating exemplar, this report will highlight the challenges of modeling novel infectious diseases while introducing ways to incorporate NN approximations to MFE. Prior to embarking on a Bayesian calibration, we first explored methods to augment the standard (non-Bayesian) UDE training procedure to account for uncertainty and increase robustness of training. In addition, it is often the case that uncertainty in observations is significant; this may be due to randomness or lack of precision in the measurement process. This uncertainty typically manifests as “noisy” observations which deviate from a true underlying signal. To account for such variability, the NN approximation to MFE is endowed with a probabilistic representation and is updated using available observational data in a Bayesian framework. By representing the MFU explicitly and deploying an embedded, data-driven model, this approach enables an agile, expressive, and interpretable method for representing MFU. In this report we will provide evidence that Bayesian UDEs show promise as a novel framework for any science-based, data-driven MFU representation; while emphasizing that significant advances must be made in the calibration of Bayesian NNs to ensure a robust calibration procedure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Portable Parallel Algorithms and Frameworks for Exascale Graph Analytics

Graphs (or networks) are a tool used to model the interactions among various entities. Efficiently processing large graphs has recently attracted significant attention due to the applications of graphs in various domains, such as biology, chemistry, and cyber-security. Analyzing the structure and properties of these graphs is an important component of many scientific computing pipelines. With the explosion in the volume of data, graphs have become very large and can contain hundreds of billions of vertices and trillions of edges. Therefore, it is crucial to develop high-performance methods to enable graph analysis to be done quickly and energy-efficiently. Furthermore, these solutions should be highly parallel in order to take advantage of modern parallel machines. However, designing efficient solutions is not enough. With the wide variety of computing environments available, each with different programmability and performance characteristics, it is necessary to develop solutions that are portable in terms of both performance (i.e., provide theoretical guarantees) and programmability (i.e., provide high level abstractions).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

In-Situ Stress Measurements at the Utah Frontier Observatory for Research in Geothermal Energy (FORGE) Site

A scientific injection campaign was conducted at the Utah Frontier Observatory for Research in Geothermal Energy (FORGE) site in 2017 and 2019. The testing included pump-in/shut-in, pump-in/flowback, and step rate tests. Various methods have been employed to interpret the in-situ stress from the test dataset. This study focuses on methods to interpret the minimum in-situ stress from step rate, pump-in/extended shut-in tests data obtained during the stimulation of two zones in Well 58-32. This well was drilled in low-permeability granitoid. A temperature of 199 °C was recorded at the well’s total depth of 2297 m relative to the rotary Kelly bushing (RKB). The lower zone (Zone 1) consisted of 46 m of the openhole at the toe of the well. Fractures in the upper zone (Zone 2) were stimulated between 2123–2126 m measured depths (MD) behind the casing. The closure stress gradient variation depended on the depth and the injection chronology. The closure stress was found to increase with the pumping rate/volume. This stress variation could indicate that poroelastic effects (“back stress”) and the presence of adjacent natural fractures may play an important role in the interpretation of fracture closure stress. Further, progressively increasing local total stresses may, consequently, have practical applications when moderate volumes of fluid are injected in a naturally fractured or high-temperature reservoir. The alternative techniques that use pump-in/flowback tests and temperature signatures provide a valuable perspective view of the in-situ stress measurements.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

CMB-S4: Forecasting Constraints on Primordial Gravitational Waves

CMB-S4—the next-generation ground-based cosmic microwave background (CMB) experiment—is set to significantly advance the sensitivity of CMB measurements and enhance our understanding of the origin and evolution of the universe. Among the science cases pursued with CMB-S4, the quest for detecting primordial gravitational waves is a central driver of the experimental design. This work details the development of a forecasting framework that includes a power-spectrum-based semianalytic projection tool, targeted explicitly toward optimizing constraints on the tensor-to-scalar ratio, r, in the presence of Galactic foregrounds and gravitational lensing of the CMB. This framework is unique in its direct use of information from the achieved performance of current Stage 2–3 CMB experiments to robustly forecast the science reach of upcoming CMB-polarization endeavors. The methodology allows for rapid iteration over experimental configurations and offers a flexible way to optimize the design of future experiments, given a desired scientific goal. To form a closed-loop process, we couple this semianalytic tool with map-based validation studies, which allow for the injection of additional complexity and verification of our forecasts with several independent analysis methods. We document multiple rounds of forecasts for CMB-S4 using this process and the resulting establishment of the current reference design of the primordial gravitational-wave component of the Stage-4 experiment, optimized to achieve our science goals of detecting primordial gravitational waves for r > 0.003 at greater than 5σ, or in the absence of a detection, of reaching an upper limit of r < 0.001 at 95% CL.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1972

Solar Electric Propulsion System Integration Technology (SEPSIT). Volume 1: Technical summary

The use of solar electric propulsion as a means of exploring space beyond the reach of ballistic missions was investigated. The method used was to study the application of this new propulsion technology to a future flight project. A 1980 Encke rendezvous mission was chosen because a design successful for Encke could be used for less difficult, but scientifically rewarding, missions. Design points for the mission and for the thrust subsystem were specified. The baseline-vehicle design was defined. A preliminary functional description document for the thrust subsystem was originated. Analyses were performed in support of the design point selection for the SEP-module thrust subsystem to specify parameters, to clarify and optimize the interface requirements, and to assure feasibility of some of the more critical technological aspects of SEP application.

Gardner, J. A.↗